1. Field
The embodiments relate to an orthogonal frequency division multiple access (OFDMA) technology applied, for example, to wireless communication systems.
2. Description of the Related Art
Increasing number of users demanding wireless Internet access and a growing number of wireless applications require high speed transmission and efficient utilization of system resources such as power and bandwidth. Orthogonal frequency division multiplexing (OFDM) is a multicarrier transmission technique that is proposed for high speed wireless transmission. It is based on a large number of orthogonal subchannels, each working at a different frequency. OFDM is originally proposed to combat inter symbol interference and frequency selective fading. However it also has a potential for a multiple access scheme, where the subchannels are shared among the competing users. OFDM-based multiple access can also be performed with power control, which adds a degree of flexibility.
In multiple access resource allocation, three main aspects are considered. The first one is spectral efficiency, which means achieving a maximum total throughput with available bandwidth and power. In Time Division Multiple Access (TDMA) transmission, spectral efficiency can be achieved by always allowing the user with the best channel to transmit. In OFDM, each subcarrier experiences a different fading depending on the user, which makes the spectral efficiency to be a more complex problem. The second issue is fairness. If the channel conditions are independent and identically distributed, all users eventually will get the same service, hence fairness is maintained. This is called multiuser diversity. On the other hand, if the distance attenuations of users are different, then some users can get more service than others. Therefore, scheduling algorithms try to provide fairness among nodes. The third important issue is satisfying quality of service (QoS) requirements. An example of QoS requirements can be bounds on delay and/or packet drop limitations for real time applications.
A proportional fair scheduler has been proposed for single carrier systems. The proposed proportional fair scheduler system may work in the context of a High Data Rate (HDR) system. The system is designed for data transfer applications (e.g. FTP and Internet). Users are scheduled to transmit at each time slot and any positive change of one user's rate results in a negative overall change of rates of the other users in the system. The proposed proportional fair scheduler for a single carrier allocates the bandwidth and power to maximize the sum of the logarithms of average user rates:
                    P        =                  arg          ⁢                                          ⁢                                    max              S                        ⁢                                          ∑                                  i                  =                  1                                N                            ⁢                                                          ⁢                              ln                ⁢                                                                  ⁢                                  R                  i                                      (                    S                    )                                                                                                          (        1        )            where {1, 2, . . . , N} is the user set and Ri(S) is the average rate of user i by scheduling policy S. The proportional fairness is achieved by scheduling at each time slot t, a user j according to:
                    j        =                  arg          ⁢                                          ⁢                                    max              i                        ⁢                                                                                r                    i                                    ⁡                                      (                    t                    )                                                                                        R                    i                                    ⁡                                      (                    t                    )                                                              .                                                          (        2        )            
Here ri(t) is an instantaneous transmittable rate to user i at the current slot, and Ri(t) is an average data rate that user i has received over time. At each time slot, the average data rate is updated according to the following rule:Ri(t+1)=αRi(t)+(1−α)ri(t)  (3)
In a proportional fair scheme T=1/(1−α) is the length of the sliding time window, and the average rate is computed over this time slot for each time slot. For example, in one proposed single carrier system, α was taken as 0.999. This method maintains fairness in the long run, while trying to schedule the user with the best channel at each slot.
Recently, the proportional fair scheduling has been proposed for multicarrier systems. However, other existing multicarrier systems proposals for proportional fair scheduling do not take into consideration power control and cannot determine the optimum bandwidth allocation when the transmission power can be dynamically assigned. Other proposals discuss the proportional fair scheduling for a single time instant, rather than the long term received rates. Besides, none of the proposals address the real time traffic (e.g., the voice and video data transfer) which has other QoS requirements than the non-real time data transfer.
A major drawback of existing proportional fair scheduling is that it assumes there are infinite packets to be transmitted at time zero and no packet arrivals. This is more suitable for an FTP session where large files can be assumed to be ready to transmit, however not suitable for real time applications such as Voice over Internet Protocol (VoIP) and video streaming. Since different real time applications can have different arrival rates, average service rates corresponding to the real time applications in the long run should be larger than the arrival rate for each session in order to maintain stability. It has been demonstrated that traditional proportional fair scheduling does not ensure stability of queues in some situations.
Another drawback of the existing proportional fair scheduling is that it does not support heterogeneous QoS requirements. For example, in VoIP and Video Streaming applications, there is a delay requirement for each packet. If a packet can not be transmitted in a certain time interval, then that packet has to be dropped, which degrades the quality of real time sessions. In proportional fair scheduling, the time window is very large, and, therefore, there is a long term rate requirement. In real time sessions, a short term rate requirement may occur.
Some existing proposals consider OFDMA based resource allocation without the proportional fairness objective. For example, a proposed subcarrier and bit allocation method aims to satisfy rate requirements of users with a minimum total power. The maximizing total throughput subject to power and subcarrier constraints is addressed, but not for the real time traffic. One existing proposal describes that a proportional rate constraint requires the rates of individual users has to be in certain proportions in order to maintain fairness. However, this approach also doesn't guarantee any short or long term transmission rates. There are also proposals directed to other schemes, such as, Code Division Multiple Access (CDMA). One existing CDMA proposal is directed to a fair queueing scheme with time varying weight assignment, wherein weights are proportional to the channel conditions divided by previously received rates. That is, a base station chooses one mobile station (user) with the highest ratio between the highest usable transmission rate and actual transmission rate, and uses all the power and the bandwidth necessary to transmit to that mobile station in the next time slot. This CDMA proposal focuses on one user but not to scheduling multiple users in the same time slot, and no QoS constraints are satisfied. Another method maximizes throughput (rates) subject to total power and bandwidth constraints in a single time slot.
The optimization problem for a single time slot, models the proportional fairness as follows. Maximize:
                                          C            ⁡                          (                              w                ,                P                            )                                =                                    ∑                              i                =                1                            M                        ⁢                                                  ⁢                          ln              ⁡                              (                                                      r                    i                                    ⁡                                      (                                                                  w                        i                                            ,                                              p                        i                                                              )                                                  )                                                    ⁢                                  ⁢                  subject          ⁢                                          ⁢          to                ⁢                                  ⁢                              P            ≥                                          ∑                                  i                  =                  1                                M                            ⁢                                                          ⁢                              p                i                                              ,                      W            ≥                                          ∑                                  i                  =                  1                                M                            ⁢                                                          ⁢                              w                i                                              ,                                    and              ⁢                                                          ⁢                              p                i                                      ≥            0                    ,                                    w              i                        ≥            0                    ,                      ∀            i                                              (        4        )            where ri(wi,pi) is the rate function. The existing scheduling methods may optimize the proportional fairness for a single time slot, but not in a long term (over multiple time slots), and cannot meet the requirements of a real time traffic such as VoIP.
IEEE 802.16 standards define the air interface and medium access control (MAC) specifications for wireless metropolitan area networks. Such networks intend to provide high speed on demand voice, data, and video streaming services for end users. IEEE 802.16 standard is often referred to as WiMax and it provides substantially higher rates than typical cellular networks. Besides WiMax eliminates the costly infrastructure to deploy cables, therefore becoming an alternative to cabled networks, such as fiber optic and DSL systems. The OFDM and OFDMA version of 802.16 systems working under 6 GHz are examples of systems that are suitable for non line of sight (NLOS) communications. WiMax networks are designed for point to multipoint communications, where a base station (BS) transmits to and receives from multiple subscriber stations (SS) and/or mobile stations (MSs) in the base station's coverage area. A SS is fixed and can be either an end user itself, or be the backbone connection of a WLAN.